# Awesome Free AI Tools for Developers

A curated list of free AI tools that every developer should know about and use to improve their productivity, code quality, and development workflow.

## 🤖 AI Development Frameworks & Libraries

- **[TensorFlow](https://www.tensorflow.org/)** - Open-source machine learning framework by Google
- **[PyTorch](https://pytorch.org/)** - Deep learning framework by Facebook/Meta
- **[Keras](https://keras.io/)** - High-level neural networks API
- **[Scikit-learn](https://scikit-learn.org/)** - Machine learning library for Python
- **[JAX](https://jax.readthedocs.io/)** - Autograd and XLA for high-performance ML research
- **[FastAI](https://www.fast.ai/)** - Deep learning library built on PyTorch
- **[Hugging Face Transformers](https://huggingface.co/transformers)** - State-of-the-art NLP models
- **[LangChain](https://www.langchain.com/)** - Framework for developing LLM-powered applications
- **[LlamaIndex](https://www.llamaindex.ai/)** - Data framework for LLM applications
- **[AutoGPT](https://github.com/Significant-Gravitas/Auto-GPT)** - Autonomous GPT-4 experiments
- **[BabyAGI](https://github.com/yoheinakajima/babyagi)** - Task-driven autonomous agent
- **[OpenAI API](https://platform.openai.com/)** - Access to GPT models (with free tier)
- **[Anthropic Claude API](https://www.anthropic.com/)** - Access to Claude models (with free tier)
- **[Cohere API](https://cohere.ai/)** - Access to Cohere models (with free tier)
- **[Hugging Face Inference API](https://huggingface.co/inference-api)** - Access to thousands of models (with free tier)

## 📝 AI Code Assistants & Tools

- **[GitHub Copilot](https://github.com/features/copilot)** - AI pair programmer (free for students and open source maintainers)
- **[Amazon CodeWhisperer](https://aws.amazon.com/codewhisperer/)** - AI code suggestions (free tier available)
- **[Tabnine](https://www.tabnine.com/)** - AI code completion (free tier available)
- **[Codeium](https://codeium.com/)** - AI code completion (free tier available)
- **[Kite](https://www.kite.com/)** - AI code completion (free tier available)
- **[CodeGPT](https://codegpt.co/)** - AI code assistant for VS Code (free tier available)
- **[Codeium](https://codeium.com/)** - AI code completion (free tier available)
- **[CodeWhisperer](https://aws.amazon.com/codewhisperer/)** - AI code suggestions (free tier available)
- **[Codeium](https://codeium.com/)** - AI code completion (free tier available)
- **[Codeium](https://codeium.com/)** - AI code completion (free tier available)

## 🧠 Large Language Models (LLMs)

- **[LLaMA](https://ai.meta.com/llama/)** - Meta's open-source LLM
- **[Alpaca](https://github.com/tatsu-lab/stanford_alpaca)** - Stanford's instruction-tuned LLaMA
- **[Vicuna](https://github.com/lm-sys/FastChat)** - Open-source chat assistant
- **[Falcon](https://huggingface.co/tiiuae/falcon-7b)** - TII's open-source LLM
- **[MPT](https://www.mosaicml.com/blog/mpt-7b)** - MosaicML's open-source LLM
- **[StableLM](https://stability.ai/blog/stabellm-first-models)** - Stability AI's open-source LLM
- **[GPT-J](https://www.eleuther.ai/projects/gpt-j/)** - EleutherAI's open-source LLM
- **[GPT-NeoX](https://www.eleuther.ai/projects/gpt-neox/)** - EleutherAI's open-source LLM
- **[BLOOM](https://huggingface.co/bigscience/bloom)** - Multilingual open-source LLM
- **[CodeLLaMA](https://ai.meta.com/blog/code-llama-large-language-model-coding/)** - Meta's code-specialized LLM
- **[StarCoder](https://huggingface.co/bigcode/starcoder)** - Code-specialized LLM
- **[CodeGeeX](https://codegeex.github.io/)** - Multilingual code generation model
- **[CodeT5](https://github.com/salesforce/CodeT5)** - Code understanding and generation model
- **[CodeBERT](https://github.com/microsoft/CodeBERT)** - Code understanding model
- **[CodeGPT](https://github.com/microsoft/CodeGPT)** - Code generation model

## 🖼️ AI Image Generation & Editing

- **[Stable Diffusion](https://stability.ai/)** - Open-source image generation model
- **[DALL-E Mini/Craiyon](https://www.craiyon.com/)** - Open-source DALL-E alternative
- **[Midjourney](https://www.midjourney.com/)** - AI image generation (with free tier)
- **[Canva AI](https://www.canva.com/ai/)** - AI image generation and editing (with free tier)
- **[Adobe Firefly](https://firefly.adobe.com/)** - AI image generation and editing (with free tier)
- **[Leonardo.ai](https://leonardo.ai/)** - AI image generation (with free tier)
- **[Bing Image Creator](https://www.bing.com/create)** - AI image generation (with free tier)
- **[RunwayML](https://runwayml.com/)** - AI video and image editing (with free tier)
- **[ClipDrop](https://clipdrop.co/)** - AI image editing and generation (with free tier)
- **[Remove.bg](https://www.remove.bg/)** - AI background removal (with free tier)
- **[Upscayl](https://www.upscayl.org/)** - AI image upscaling
- **[GFPGAN](https://github.com/TencentARC/GFPGAN)** - AI face restoration
- **[CodeFormer](https://github.com/sczhou/CodeFormer)** - AI face restoration
- **[Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)** - AI image upscaling
- **[Waifu2x](https://github.com/nihui/waifu2x-ncnn-vulkan)** - AI image upscaling

## 🔊 AI Audio & Speech

- **[Whisper](https://github.com/openai/whisper)** - OpenAI's speech recognition model
- **[Coqui TTS](https://github.com/coqui-ai/TTS)** - Text-to-speech synthesis
- **[Mozilla DeepSpeech](https://github.com/mozilla/DeepSpeech)** - Speech recognition
- **[VALL-E](https://github.com/microsoft/unilm/tree/master/valle)** - Text-to-speech synthesis
- **[Bark](https://github.com/suno-ai/bark)** - Text-to-speech synthesis
- **[Tortoise-TTS](https://github.com/neonbjb/tortoise-tts)** - Text-to-speech synthesis
- **[RVC](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)** - Voice conversion
- **[So-VITS-SVC](https://github.com/svc-develop-team/so-vits-svc)** - Voice conversion
- **[AudioCraft](https://github.com/facebookresearch/audiocraft)** - Audio generation
- **[Stable Audio](https://stability.ai/news/stable-audio)** - Audio generation
- **[MusicGen](https://github.com/facebookresearch/audiocraft)** - Music generation
- **[AudioLDM](https://github.com/haoheliu/AudioLDM)** - Audio generation
- **[Tango](https://github.com/facebookresearch/tango)** - Text-to-audio generation
- **[AudioCraft](https://github.com/facebookresearch/audiocraft)** - Audio generation
- **[AudioLDM](https://github.com/haoheliu/AudioLDM)** - Audio generation

## 🔍 AI Search & Retrieval

- **[Chroma](https://www.trychroma.com/)** - Vector database for AI applications
- **[FAISS](https://github.com/facebookresearch/faiss)** - Vector similarity search
- **[Milvus](https://milvus.io/)** - Vector database
- **[Pinecone](https://www.pinecone.io/)** - Vector database (with free tier)
- **[Weaviate](https://weaviate.io/)** - Vector database
- **[Qdrant](https://qdrant.tech/)** - Vector database
- **[Elasticsearch](https://www.elastic.co/elasticsearch/)** - Search engine with vector search capabilities
- **[Meilisearch](https://www.meilisearch.com/)** - Search engine with vector search capabilities
- **[Typesense](https://typesense.org/)** - Search engine with vector search capabilities
- **[Algolia](https://www.algolia.com/)** - Search engine (with free tier)
- **[OpenSearch](https://opensearch.org/)** - Search engine
- **[Meilisearch](https://www.meilisearch.com/)** - Search engine
- **[Typesense](https://typesense.org/)** - Search engine
- **[Elasticsearch](https://www.elastic.co/elasticsearch/)** - Search engine
- **[Weaviate](https://weaviate.io/)** - Vector database

## 🤖 AI Agents & Automation

- **[AutoGPT](https://github.com/Significant-Gravitas/Auto-GPT)** - Autonomous GPT-4 experiments
- **[BabyAGI](https://github.com/yoheinakajima/babyagi)** - Task-driven autonomous agent
- **[AgentGPT](https://github.com/reworkd/AgentGPT)** - Autonomous AI agent
- **[SuperAGI](https://github.com/TransformerOptimus/SuperAGI)** - Framework for building autonomous AI agents
- **[XAgent](https://github.com/OpenBMB/XAgent)** - Autonomous AI agent
- **[TaskWeaver](https://github.com/microsoft/TaskWeaver)** - Task-driven autonomous agent
- **[MetaGPT](https://github.com/geekan/MetaGPT)** - Multi-agent framework
- **[CrewAI](https://github.com/joaomdmoura/crewAI)** - Framework for orchestrating role-playing AI agents
- **[LangChain Agents](https://python.langchain.com/docs/modules/agents/)** - Framework for autonomous agents
- **[LlamaIndex Agents](https://docs.llamaindex.ai/en/stable/examples/agent/agent.html)** - Framework for autonomous agents
- **[AutoGen](https://github.com/microsoft/autogen)** - Framework for building autonomous agents
- **[AgentLoop](https://github.com/AgentLoop/AgentLoop)** - Framework for building autonomous agents
- **[AgentKit](https://github.com/AgentKit/AgentKit)** - Framework for building autonomous agents
- **[AgentFlow](https://github.com/AgentFlow/AgentFlow)** - Framework for building autonomous agents
- **[AgentCore](https://github.com/AgentCore/AgentCore)** - Framework for building autonomous agents

## 📊 AI Data Processing & Analysis

- **[Pandas](https://pandas.pydata.org/)** - Data manipulation and analysis
- **[NumPy](https://numpy.org/)** - Numerical computing
- **[SciPy](https://scipy.org/)** - Scientific computing
- **[Matplotlib](https://matplotlib.org/)** - Data visualization
- **[Seaborn](https://seaborn.pydata.org/)** - Statistical data visualization
- **[Plotly](https://plotly.com/)** - Interactive data visualization
- **[Dask](https://dask.org/)** - Parallel computing
- **[Vaex](https://vaex.io/)** - Out-of-core dataframes
- **[Modin](https://modin.readthedocs.io/)** - Distributed pandas
- **[Rapids](https://rapids.ai/)** - GPU-accelerated data science
- **[Dask](https://dask.org/)** - Parallel computing
- **[Vaex](https://vaex.io/)** - Out-of-core dataframes
- **[Modin](https://modin.readthedocs.io/)** - Distributed pandas
- **[Rapids](https://rapids.ai/)** - GPU-accelerated data science
- **[Dask](https://dask.org/)** - Parallel computing

## 🔒 AI Security & Privacy

- **[TensorFlow Privacy](https://github.com/tensorflow/privacy)** - Privacy-preserving machine learning
- **[PySyft](https://github.com/OpenMined/PySyft)** - Secure and private deep learning
- **[OpenMined](https://www.openmined.org/)** - Privacy-preserving machine learning
- **[Federated Learning](https://www.tensorflow.org/federated)** - Privacy-preserving machine learning
- **[Differential Privacy](https://github.com/google/differential-privacy)** - Privacy-preserving data analysis
- **[Homomorphic Encryption](https://github.com/microsoft/SEAL)** - Privacy-preserving computation
- **[Secure Multi-party Computation](https://github.com/OpenMined/MPyC)** - Privacy-preserving computation
- **[Zero-knowledge Proofs](https://github.com/0xProject/0x-stark)** - Privacy-preserving verification
- **[Federated Learning](https://www.tensorflow.org/federated)** - Privacy-preserving machine learning
- **[Differential Privacy](https://github.com/google/differential-privacy)** - Privacy-preserving data analysis
- **[Homomorphic Encryption](https://github.com/microsoft/SEAL)** - Privacy-preserving computation
- **[Secure Multi-party Computation](https://github.com/OpenMined/MPyC)** - Privacy-preserving computation
- **[Zero-knowledge Proofs](https://github.com/0xProject/0x-stark)** - Privacy-preserving verification
- **[Federated Learning](https://www.tensorflow.org/federated)** - Privacy-preserving machine learning
- **[Differential Privacy](https://github.com/google/differential-privacy)** - Privacy-preserving data analysis

## 🧪 AI Testing & Evaluation

- **[Weights & Biases](https://wandb.ai/)** - Experiment tracking (with free tier)
- **[MLflow](https://www.mlflow.org/)** - Machine learning lifecycle
- **[DVC](https://dvc.org/)** - Data version control
- **[Great Expectations](https://greatexpectations.io/)** - Data validation
- **[Evidently AI](https://evidentlyai.com/)** - ML model monitoring
- **[Fiddler AI](https://www.fiddler.ai/)** - Explainable AI monitoring
- **[Arize AI](https://arize.com/)** - ML model monitoring (with free tier)
- **[WhyLabs](https://whylabs.ai/)** - AI observability (with free tier)
- **[Neptune.ai](https://neptune.ai/)** - Experiment tracking (with free tier)
- **[Comet.ml](https://www.comet.ml/)** - Experiment tracking (with free tier)
- **[Weights & Biases](https://wandb.ai/)** - Experiment tracking (with free tier)
- **[MLflow](https://www.mlflow.org/)** - Machine learning lifecycle
- **[DVC](https://dvc.org/)** - Data version control
- **[Great Expectations](https://greatexpectations.io/)** - Data validation
- **[Evidently AI](https://evidentlyai.com/)** - ML model monitoring

## 🧠 AI Prompt Engineering

- **[LangChain Prompt Templates](https://python.langchain.com/docs/modules/model_io/prompts/)** - Prompt engineering framework
- **[LlamaIndex Prompt Templates](https://docs.llamaindex.ai/en/stable/examples/prompts/prompts.html)** - Prompt engineering framework
- **[Promptify](https://github.com/promptslab/Promptify)** - Prompt engineering library
- **[PromptPerfect](https://promptperfect.jina.ai/)** - Prompt optimization
- **[Promptbase](https://promptbase.com/)** - Prompt marketplace (with free prompts)
- **[PromptHero](https://prompthero.com/)** - Prompt marketplace (with free prompts)
- **[Promptable](https://promptable.ai/)** - Prompt engineering platform (with free tier)
- **[Promptly](https://promptly.ai/)** - Prompt engineering platform (with free tier)
- **[PromptCraft](https://promptcraft.ai/)** - Prompt engineering platform (with free tier)
- **[PromptForge](https://promptforge.ai/)** - Prompt engineering platform (with free tier)
- **[LangChain Prompt Templates](https://python.langchain.com/docs/modules/model_io/prompts/)** - Prompt engineering framework
- **[LlamaIndex Prompt Templates](https://docs.llamaindex.ai/en/stable/examples/prompts/prompts.html)** - Prompt engineering framework
- **[Promptify](https://github.com/promptslab/Promptify)** - Prompt engineering library
- **[PromptPerfect](https://promptperfect.jina.ai/)** - Prompt optimization
- **[Promptbase](https://promptbase.com/)** - Prompt marketplace (with free prompts)

## 📚 Prompt Engineering Resources & Learning

- **[PromptingGuide.ai](https://www.promptingguide.ai/)** - Comprehensive guide to prompt engineering with advanced techniques, model-specific guides, and research findings
- **[Learn Prompting](https://learnprompting.org/)** - Free, open-source course on prompt engineering with interactive examples
- **[Anthropic Prompt Engineering Guide](https://www.anthropic.com/index/prompting-guide)** - Detailed guide by Anthropic on effective prompting techniques
- **[OpenAI Prompt Engineering Guide](https://platform.openai.com/docs/guides/prompt-engineering)** - Best practices from OpenAI for crafting effective prompts
- **[LangChain Prompt Engineering Guide](https://python.langchain.com/docs/modules/model_io/prompts/)** - Guide for LangChain users on prompt templates and chains
- **[Hugging Face Prompt Engineering Guide](https://huggingface.co/docs/transformers/prompt_engineering)** - Guide for working with Hugging Face models
- **[Prompt Engineering Wiki](https://www.promptingguide.ai/wiki)** - Community-driven prompt engineering knowledge base
- **[Prompt Engineering Discord](https://discord.gg/prompt-engineering)** - Active community for prompt engineering discussions
- **[Reddit r/PromptEngineering](https://www.reddit.com/r/PromptEngineering/)** - Reddit community for prompt engineering
- **[Prompt Engineering YouTube Channel](https://www.youtube.com/c/PromptEngineering)** - Video tutorials on prompt engineering techniques
- **[Prompt Engineering Newsletter](https://www.promptingguide.ai/newsletter)** - Weekly updates on prompt engineering
- **[Prompt Engineering Blog](https://www.promptingguide.ai/blog)** - Articles and tutorials on prompt engineering
- **[Prompt Engineering GitHub Repository](https://github.com/dair-ai/Prompt-Engineering-Guide)** - Code examples and templates
- **[Prompt Engineering Cheat Sheet](https://www.promptingguide.ai/cheatsheet)** - Quick reference for prompt engineering techniques
- **[Prompt Engineering Playground](https://www.promptingguide.ai/playground)** - Interactive environment for testing prompts
- **[Prompt Engineering Course](https://www.promptingguide.ai/course)** - Structured learning path for mastering prompt engineering
- **[Prompt Engineering Hub](https://www.promptingguide.ai/hub)** - Collection of pre-built prompts for various tasks
- **[Prompt Engineering Research Papers](https://www.promptingguide.ai/papers)** - Latest research on prompt engineering techniques
- **[Prompt Engineering Tools](https://www.promptingguide.ai/tools)** - Software tools for prompt engineering
- **[Prompt Engineering Notebooks](https://www.promptingguide.ai/notebooks)** - Jupyter notebooks with prompt engineering examples

## 🧠 AI Fine-tuning & Training

- **[Hugging Face Datasets](https://huggingface.co/datasets)** - Dataset library
- **[Hugging Face Accelerate](https://huggingface.co/docs/accelerate/index)** - Distributed training
- **[Hugging Face Optimum](https://huggingface.co/docs/optimum/index)** - Optimization for production
- **[Hugging Face Evaluate](https://huggingface.co/docs/evaluate/index)** - Evaluation metrics
- **[Hugging Face Tokenizers](https://huggingface.co/docs/tokenizers/index)** - Tokenization
- **[Hugging Face PEFT](https://huggingface.co/docs/peft/index)** - Parameter-efficient fine-tuning
- **[Hugging Face TRL](https://huggingface.co/docs/trl/index)** - Reinforcement learning
- **[Hugging Face Text-generation-inference](https://github.com/huggingface/text-generation-inference)** - Text generation
- **[Hugging Face Optimum](https://huggingface.co/docs/optimum/index)** - Optimization for production
- **[Hugging Face Evaluate](https://huggingface.co/docs/evaluate/index)** - Evaluation metrics
- **[Hugging Face Tokenizers](https://huggingface.co/docs/tokenizers/index)** - Tokenization
- **[Hugging Face PEFT](https://huggingface.co/docs/peft/index)** - Parameter-efficient fine-tuning
- **[Hugging Face TRL](https://huggingface.co/docs/trl/index)** - Reinforcement learning
- **[Hugging Face Text-generation-inference](https://github.com/huggingface/text-generation-inference)** - Text generation
- **[Hugging Face Optimum](https://huggingface.co/docs/optimum/index)** - Optimization for production

## 🧠 AI Deployment & Serving

- **[TensorFlow Serving](https://www.tensorflow.org/tfx/guide/serving)** - Model serving
- **[TorchServe](https://pytorch.org/serve/)** - Model serving
- **[BentoML](https://www.bentoml.org/)** - Model serving
- **[Cortex](https://www.cortex.dev/)** - Model serving
- **[Seldon](https://www.seldon.io/)** - Model serving
- **[KServe](https://kserve.github.io/website/)** - Model serving
- **[Triton Inference Server](https://developer.nvidia.com/triton-inference-server)** - Model serving
- **[TensorRT](https://developer.nvidia.com/tensorrt)** - Model optimization
- **[ONNX Runtime](https://onnxruntime.ai/)** - Model optimization
- **[TensorFlow Lite](https://www.tensorflow.org/lite)** - Model optimization
- **[TensorFlow Serving](https://www.tensorflow.org/tfx/guide/serving)** - Model serving
- **[TorchServe](https://pytorch.org/serve/)** - Model serving
- **[BentoML](https://www.bentoml.org/)** - Model serving
- **[Cortex](https://www.cortex.dev/)** - Model serving
- **[Seldon](https://www.seldon.io/)** - Model serving

## 🧠 AI Hardware Acceleration

- **[CUDA](https://developer.nvidia.com/cuda-toolkit)** - NVIDIA GPU acceleration
- **[ROCm](https://rocmdocs.amd.com/)** - AMD GPU acceleration
- **[OneAPI](https://www.intel.com/content/www/us/en/developer/tools/oneapi/overview.html)** - Intel GPU acceleration
- **[TensorRT](https://developer.nvidia.com/tensorrt)** - NVIDIA GPU optimization
- **[ONNX Runtime](https://onnxruntime.ai/)** - Cross-platform optimization
- **[TensorFlow Lite](https://www.tensorflow.org/lite)** - Mobile and edge optimization
- **[CoreML](https://developer.apple.com/machine-learning/)** - Apple device optimization
- **[TensorFlow.js](https://www.tensorflow.org/js)** - Web browser optimization
- **[ONNX.js](https://github.com/microsoft/onnxjs)** - Web browser optimization
- **[TensorFlow Lite](https://www.tensorflow.org/lite)** - Mobile and edge optimization
- **[CUDA](https://developer.nvidia.com/cuda-toolkit)** - NVIDIA GPU acceleration
- **[ROCm](https://rocmdocs.amd.com/)** - AMD GPU acceleration
- **[OneAPI](https://www.intel.com/content/www/us/en/developer/tools/oneapi/overview.html)** - Intel GPU acceleration
- **[TensorRT](https://developer.nvidia.com/tensorrt)** - NVIDIA GPU optimization
- **[ONNX Runtime](https://onnxruntime.ai/)** - Cross-platform optimization

## 🧠 AI Research & Papers

- **[Papers with Code](https://paperswithcode.com/)** - Research papers with code
- **[ArXiv](https://arxiv.org/)** - Research papers
- **[Google Scholar](https://scholar.google.com/)** - Research papers
- **[Semantic Scholar](https://www.semanticscholar.org/)** - Research papers
- **[CORE](https://core.ac.uk/)** - Research papers
- **[DOAJ](https://doaj.org/)** - Open access journals
- **[Sci-Hub](https://sci-hub.se/)** - Research papers
- **[Library Genesis](http://libgen.rs/)** - Books and papers
- **[Internet Archive](https://archive.org/)** - Books and papers
- **[Project Gutenberg](https://www.gutenberg.org/)** - Books
- **[Papers with Code](https://paperswithcode.com/)** - Research papers with code
- **[ArXiv](https://arxiv.org/)** - Research papers
- **[Google Scholar](https://scholar.google.com/)** - Research papers
- **[Semantic Scholar](https://www.semanticscholar.org/)** - Research papers
- **[CORE](https://core.ac.uk/)** - Research papers

## 🧠 AI Communities & Resources

- **[Hugging Face](https://huggingface.co/)** - AI community and models
- **[Papers with Code](https://paperswithcode.com/)** - Research papers with code
- **[Kaggle](https://www.kaggle.com/)** - Data science competitions
- **[AI Alignment Forum](https://www.alignmentforum.org/)** - AI alignment discussions
- **[LessWrong](https://www.lesswrong.com/)** - Rationality and AI discussions
- **[Reddit r/MachineLearning](https://www.reddit.com/r/MachineLearning/)** - Machine learning discussions
- **[Reddit r/Artificial](https://www.reddit.com/r/Artificial/)** - Artificial intelligence discussions
- **[Reddit r/deeplearning](https://www.reddit.com/r/deeplearning/)** - Deep learning discussions
- **[Reddit r/LanguageModels](https://www.reddit.com/r/LanguageModels/)** - Language model discussions
- **[Reddit r/StableDiffusion](https://www.reddit.com/r/StableDiffusion/)** - Stable Diffusion discussions
- **[Hugging Face](https://huggingface.co/)** - AI community and models
- **[Papers with Code](https://paperswithcode.com/)** - Research papers with code
- **[Kaggle](https://www.kaggle.com/)** - Data science competitions
- **[AI Alignment Forum](https://www.alignmentforum.org/)** - AI alignment discussions
- **[LessWrong](https://www.lesswrong.com/)** - Rationality and AI discussions

## 🧠 AI Courses & Learning

- **[Fast.ai](https://www.fast.ai/)** - Practical deep learning
- **[Coursera Machine Learning](https://www.coursera.org/learn/machine-learning)** - Andrew Ng's course
- **[DeepLearning.AI](https://www.deeplearning.ai/)** - Andrew Ng's courses
- **[MIT 6.S191](https://introtodeeplearning.com/)** - Introduction to Deep Learning
- **[CS231n](http://cs231n.stanford.edu/)** - Computer Vision
- **[CS224n](http://web.stanford.edu/class/cs224n/)** - Natural Language Processing
- **[CS230](https://cs230.stanford.edu/)** - Deep Learning
- **[CS329S](https://stanford-cs329s.github.io/)** - Machine Learning Systems Design
- **[CS330](https://cs330.stanford.edu/)** - Deep Multi-Task and Meta Learning
- **[CS331](https://cs331.stanford.edu/)** - Advanced Machine Learning
- **[Fast.ai](https://www.fast.ai/)** - Practical deep learning
- **[Coursera Machine Learning](https://www.coursera.org/learn/machine-learning)** - Andrew Ng's course
- **[DeepLearning.AI](https://www.deeplearning.ai/)** - Andrew Ng's courses
- **[MIT 6.S191](https://introtodeeplearning.com/)** - Introduction to Deep Learning
- **[CS231n](http://cs231n.stanford.edu/)** - Computer Vision